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Conference Paper
A Data Cube Model for Surveillance Video Indexing and Retrieval
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- Authors
- Hansung Lee, Sohee Park, Jang-Hee Yoo
- Issue Date
- 2013-07
- Citation
- International Conference on Signal Processing and Multimedia Applications (SIGMAP) 2013, pp.1-6
- Language
- English
- Type
- Conference Paper
- Abstract
- We propose a novel data cube model, viz., SurvCube, for the multi-dimensional indexing and retrieval of surveillance videos. The proposed method provides the multi-dimensional analysis of interesting objects in surveillance videos according to the chronological view, events and locations by means of data cube structure. By employing the OLAP operation on the surveillance videos, it is able to provides desirable functionalities such as 1) retrieval of objects and events at a different level of abstraction, i.e., coarse to fine grained retrieval; 2) providing the tracing of interesting object trajectories across the cameras; 3) providing the summarization of surveillance video with respect to interesting objects (and/or events) and abstract level of time and locations.
- KSP Keywords
- Cube model, Data cube, Fine grained(FG), Indexing and retrieval, Level of abstraction, Multi-dimensional indexing, Object trajectories, Surveillance video, Video indexing, coarse-to-fine, different levels